Skip to main content

​
1. Use Descriptive Names

Tool names come from function/method names. Use clear, descriptive names: 
# Good
@tool
def search_customer_database(query: str) -> str:
    """Search for customers by name or ID."""
    ...

# Avoid
@tool
def search(q: str) -> str:
    """Search."""
    ...

​
2. Provide Comprehensive Docstrings

Docstrings become the tool description shown to the LLM: 
@tool
def calculate_shipping(
    weight_kg: float,
    destination_country: str,
    express: bool = False
) -> dict:
    """
    Calculate shipping cost for a package.

    Args:
        weight_kg: Package weight in kilograms (must be > 0)
        destination_country: ISO 3166-1 alpha-2 country code (e.g., "US", "DE")
        express: Whether to use express shipping (2-3 days vs 7-10 days)

    Returns:
        Dictionary with 'cost', 'currency', and 'estimated_days'
    """
    ...
Use ToolKit for related tools that share state: 
from upsonic.tools import ToolKit, tool

class DatabaseToolKit(ToolKit):
    def __init__(self, connection_string: str):
        self.conn = connect(connection_string)

    @tool
    def query(self, sql: str) -> list:
        """Execute a SQL query."""
        return self.conn.execute(sql).fetchall()

    @tool
    def insert(self, table: str, data: dict) -> int:
        """Insert a row into a table."""
        ...

​
4. Remove Unused Tools

Remove tools when no longer needed to keep the LLM focused: 
# After completing data import, remove import tools
agent.remove_tools(["import_csv", "validate_schema"])

# Keep only the tools needed for the next phase